Building your own predictions (Open Source)

For users with specific requirements or the technical capacity to develop their own solutions, Forest Foresight provides an open source scripting package. This powerful option allows users to harness the full potential of Forest Foresight's methodology while maintaining complete control over the prediction process. If you want to explore this option first see if you have the necessary skills to work with the Forest Foresight package here: Open Source Skill level Test

Key Features and Benefits:

1. Access to Core Algorithms:
   Users can directly interact with the fundamental algorithms that drive Forest Foresight's predictions, enabling a deep understanding of the tool's inner workings.

2. Customization and Adaptation:
   The open-source nature allows for modification and adaptation of the tool to meet specific needs or account for local conditions. This flexibility is crucial for addressing unique deforestation scenarios.

3. Custom Predictions:
   Users can develop tailored predictions by incorporating their own data inputs, potentially improving accuracy for specific regions or integrating novel data sources. When integrating your own datasets, please also have a look at what high-quality new datasets would look like here: Enhancing Forest Foresight with High Quality Datasets

4. Full Control:
   This approach empowers users with complete control over the entire prediction process, from data preparation to final output generation.

5. Training and Support:
   WWF offers comprehensive training to help users maximize the potential of the open-source package. This ensures that even those new to the system can effectively leverage its capabilities.

6. GNU GPLv3 License:
   The package is released under the GNU General Public License version 3, ensuring it remains free and open for use, modification, and distribution.

7. Extensive Resources:
   Detailed information, tutorials, and best practices can be found in the Resources and Training Material sections of the Forest Foresight website.

8. GitHub Access:
   The complete source code and documentation are available on GitHub, fostering collaboration and continuous improvement of the tool.

9. Easy Installation:
   Users can easily install the package in R using devtools. The package is available at GitHub - ForestForesight/ForestForesight: second edition of ForestForesight

This open-source option is ideal for organizations and researchers who want to dive deep into deforestation prediction, customize the tool to their specific contexts, or integrate Forest Foresight's capabilities into larger environmental monitoring systems. By providing this level of access and flexibility, Forest Foresight encourages innovation and adaptation in the crucial field of deforestation prediction and monitoring.